model releases

Iranian media: Iran launches 'Hormuz Safe', a Bitcoin-backed insurance service for shipping companies transiting the Strait of Hormuz; ~1,500 ships are trapped (Golnar Motevalli/Bloomberg)

Golnar Motevalli / Bloomberg: Iranian media: Iran launches “Hormuz Safe”, a Bitcoin-backed insurance service for shipping companies transiting the Strait of Hormuz; ~1,500 ships are trapped — Iran has

model-releasestechmeme

Judge Circuits

arXiv:2605.16023v1 Announce Type: new Abstract: LLM-as-a-judge has become the dominant paradigm for grading model outputs at scale, yet the same model assigns systematically different scores when its

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization

arXiv:2603.25099v2 Announce Type: replace-cross Abstract: We present a framework in which a large language model (LLM) acts as an online adaptive controller for SIMP topology optimization, replacing c

Large Language Models Could Be Rote Learners

arXiv:2504.08300v5 Announce Type: replace-cross Abstract: Benchmark-based evaluation, e.g., multiple-choice questions (MCQs) and open-ended questions (OEQs), is widely used for evaluating Large Langua

LASER: Language Model Regression for Semi-Structured Workflow Resource and Runtime Estimation

arXiv:2512.19701v2 Announce Type: replace-cross Abstract: Accurate prediction of resource consumption and runtime for cloud workflow jobs is critical for scheduling efficiency, yet remains challenging

Layer Equivalence Is Not a Property of Layers Alone: How You Test Redundancy Changes What You Find

arXiv:2605.16234v1 Announce Type: cross Abstract: When researchers ask whether two transformer layers are 'equivalent' for compression, they often conflate distinct tests. Replacement asks whether one

Learn2Splat: Extending the Horizon of Learned 3DGS Optimization

arXiv:2605.15760v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) optimization is most commonly performed using standard optimizers (Adam, SGD). While stable across diverse scenes, standard

Learning Disentangled Representations for Generalized Multi-view Clustering

arXiv:2605.15640v1 Announce Type: new Abstract: Multi-View Clustering (MVC) has gained significant attention for its ability to leverage complementary information across diverse views. However, existi

Learning Dynamic Structural Specialization for Underwater Salient Object Detection

arXiv:2605.15535v1 Announce Type: new Abstract: Underwater salient object detection (USOD) has attracted increasing attention for underwater visual scene understanding and vision-guided robotic applic

Learning Selective Merge Policies for Deadline-Constrained Coded Caching via Deep Reinforcement Learning

arXiv:2605.15236v1 Announce Type: cross Abstract: With the coded caching, the server can use the information the users have cached to serve multiple users at a time by sending a single coded multi-cas

Learning Structured Robot Policies from Vision-Language Models via Synthetic Neuro-Symbolic Supervision

model-releasesarxiv-cs-ro

arXiv:2604.02812v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) have recently demonstrated strong capabilities in mapping multimodal observations to robot behaviors. However, most cu

llama.cpp adds MTP for the Qwen3.6 family This is a significant milestone for the local AI ecosystem. The performance jump with these change…

model-releasesclem-delangue--x

llama.cpp adds MTP for the Qwen3.6 family This is a significant milestone for the local AI ecosystem. The performance jump with these changes is massive and elevates local inference on commodity hardw

llama.cpp with MTP support makes local models fast enough to use as daily drivers 🚀 Qwen3.6-27B dense generation (on A10G): From 25 tok/s →…

model-releasesclem-delangue--x

llama.cpp with MTP support makes local models fast enough to use as daily drivers 🚀 Qwen3.6-27B dense generation (on A10G): From 25 tok/s → 45 tok/s (+78%). Two flags on llama-server: --spec-type draf

LLM-EDT: Large Language Model Enhanced Cross-domain Sequential Recommendation with Dual-phase Training

arXiv:2511.19931v2 Announce Type: replace-cross Abstract: Cross-domain Sequential Recommendation (CDSR) has been proposed to enrich user-item interactions by incorporating information from various dom

LoCO: Low-rank Compositional Rotation Fine-tuning

arXiv:2605.15916v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning (PEFT) has emerged as an critical technique for adapting large-scale foundation models across natural language process

Long Range Frequency Tuning for QML

arXiv:2602.23409v2 Announce Type: replace-cross Abstract: Angle-encoded variational quantum circuits admit a truncated Fourier series representation of their output, but approximating functions with m

Looped SSMs: Depth-Recurrence and Input Reshaping for Time Series Classification

arXiv:2605.16048v1 Announce Type: cross Abstract: State Space Models (SSMs) are inherently recurrent along the sequence dimension, yet depth-recurrence - reusing the same block repeatedly across layer

Mask-Morph Graph U-Net: A Generalisable Mesh-Based Surrogate for Crashworthiness Field Prediction under Large Geometric Variation

arXiv:2605.15231v1 Announce Type: cross Abstract: Nonlinear finite element crash simulations are accurate but computationally expensive, limiting their use in iterative design optimisation. Machine-le

Measuring Maximum Activations in Open Large Language Models

arXiv:2605.15572v1 Announce Type: new Abstract: The dynamic range of activations is a first-order constraint for low-bit quantization, activation scaling, and stable LLM inference. Prior work characte

MHGraphBench: Knowledge Graph-Grounded Benchmarking of Mental Health Knowledge in Large Language Models

arXiv:2605.15589v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in the mental health domain, yet it remains unclear how well they capture related biomedical knowledg

MI-CXR: A Benchmark for Longitudinal Reasoning over Multi-Interval Chest X-rays

arXiv:2605.15574v1 Announce Type: new Abstract: Longitudinal chest X-ray (CXR) interpretation requires reasoning over disease evolution across multiple patient visits, yet most existing medical VQA be

Minerva-Ego: Spatiotemporal Hints for Egocentric Video Understanding

arXiv:2605.15342v1 Announce Type: new Abstract: Video reasoning models are a core component of egocentric and embodied agents. However, standard benchmarks for assessing models provide only evaluation

MorphoHELM: A Comprehensive Benchmark for Evaluating Representations for Microscopy-Based Morphology Assays

arXiv:2605.15383v1 Announce Type: new Abstract: Microscopy images contain rich information about how cells respond to perturbations, making them essential to applications like drug screening. To quant

Multi-Fidelity Flow Matching: Cascaded Refinement of PDE Solutions

arXiv:2605.16118v1 Announce Type: new Abstract: The source distribution in conditional flow matching is a design parameter that can be calibrated to data, not a default isotropic prior. We exploit thi

Multi-Probe Zero Collision Hash (MPZCH): Mitigating Embedding Collisions and Enhancing Model Freshness in Large-Scale Recommenders

arXiv:2602.17050v3 Announce Type: replace Abstract: Embedding tables are critical components of large-scale recommendation systems, facilitating the efficient mapping of high-cardinality categorical f

MuteBench: Modality Unavailability Tolerance Evaluation for Incomplete Multimodal Fusion

arXiv:2605.15235v1 Announce Type: new Abstract: Multimodal physiological data powers clinical AI systems from intensive care units to wearable devices, but sensors routinely fail in practice. Two fail

MyoChallenge 2025: A New Benchmark for Human Athletic Intelligence

model-releasesarxiv-cs-ro

arXiv:2605.15650v1 Announce Type: new Abstract: Athletic performance represents the pinnacle of human motor intelligence, demanding rapid choices, precise control, agility, and coordinated physical ex

Navigating Potholes with Geometry-Aware Sharpness Minimization

arXiv:2605.16134v1 Announce Type: cross Abstract: Sharpness-aware minimization (SAM) encourages flat minima by perturbing parameters along directions of high loss curvature, but treats all parameter d

Navigating the Challenges of AI-Generated Image Detection in the Wild: What Truly Matters?

arXiv:2507.10236v2 Announce Type: replace Abstract: As generative Artificial Intelligence (AI) advances, the realism of AI generated imagery has reached a threshold capable of deceiving even vigilant

NEW paper from Meta: Agentic Discovery of Neural Architectures. This is a hot new area of research! Keep an eye on it.

NEW paper from Meta: Agentic Discovery of Neural Architectures. This is a hot new area of research! Keep an eye on it. NEW paper from Meta. (bookmark it) It's an agent system that autonomously discove

model-releasesdair-ai--x

NEW paper worth reading. GPT-5.4 nano plus a critic-comparator orchestration loop hits 76.4% on SWE-bench Verified, matching standalone Gemi…

NEW paper worth reading. GPT-5.4 nano plus a critic-comparator orchestration loop hits 76.4% on SWE-bench Verified, matching standalone Gemini 3 Pro and Claude Opus 4.5 Thinking. The trick is to selec

model-releasesdair-ai--x

Njord: A Probabilistic Graph Neural Network for Ensemble Ocean Forecasting

arXiv:2605.15470v1 Announce Type: new Abstract: Ocean dynamics are inherently chaotic, yet existing machine learning ocean models produce only deterministic forecasts. We introduce Njord, a probabilis

Offline Semantic Guidance for Efficient Vision-Language-Action Policy Distillation

arXiv:2605.16241v1 Announce Type: cross Abstract: Billion-parameter Vision-Language-Action (VLA) policies have recently shown impressive performance in robotic manipulation, yet their size and inferen

OgBench: A Framework for Evaluating Graph Neural Networks on Omics Data

arXiv:2605.15511v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have become the dominant framework for inductive graph-level learning. Yet most benchmarks focus on the regime n gg p, wher

okay this is going kinda viral and tbh my original text was kind of messy, so here's a second pass with the help of Claude: -- Implement <SP…

okay this is going kinda viral and tbh my original text was kind of messy, so here's a second pass with the help of Claude: -- Implement <SPEC>. As you work maintain a running implementation-notes.htm

model-releasesthariq--x

On RGB-TIR Stereo Calibration under Extreme Resolution Asymmetry

arXiv:2605.15860v1 Announce Type: new Abstract: Accurate geometric calibration of RGB-thermal infrared (TIR) stereo camera systems is essential for multimodal building envelope analysis, yet remains c

One thing to watch for with Claude & GPT is that the models expose too much irrelevant history in their outputs. Slides are given footers sa…

model-releasesethan-mollick--x

One thing to watch for with Claude & GPT is that the models expose too much irrelevant history in their outputs. Slides are given footers saying things like 'Better, more targeted version' if you aske

Optimizing LLM Inference: Fluid-Guided Online Scheduling with Memory Constraints

arXiv:2504.11320v3 Announce Type: replace-cross Abstract: Large language models now serve millions of users daily, with providers incurring costs exceeding $700,000 per day. Each request requires toke

PAGER: Bridging the Semantic-Execution Gap in Point-Precise Geometric GUI Control

arXiv:2605.15963v1 Announce Type: new Abstract: Large vision-language models have significantly advanced GUI agents, enabling executable interaction across web, mobile, and desktop interfaces. Yet the

Painless Activation Steering: An Automated, Lightweight Approach for Post-Training Large Language Models

arXiv:2509.22739v3 Announce Type: replace-cross Abstract: Language models (LMs) are typically post-trained for desired capabilities and behaviors via weight-based or prompt-based steering, but the for

PBT-Bench: Benchmarking AI Agents on Property-Based Testing

arXiv:2605.15229v1 Announce Type: cross Abstract: Existing code benchmarks measure whether an agent can produce any test that reproduces a known bug, or whether it can produce a patch that fixes a des

PDRNN: Modular Data-driven Pedestrian Dead Reckoning on Loosely Coupled Radio- and Inertial-Signalstreams

arXiv:2605.15252v1 Announce Type: cross Abstract: Modern pedestrian dead reckoning (PDR) systems rely on fusing noisy and biased estimates of position, velocity, and calibrated orientation derived fro

PerfCodeBench: Benchmarking LLMs for System-Level High-Performance Code Optimization

arXiv:2605.15222v1 Announce Type: cross Abstract: Large language models (LLMs) can often generate functionally correct code, but their ability to produce efficient implementations for performance-crit

Perforated Neural Networks for Keyword Spotting

arXiv:2605.15647v1 Announce Type: new Abstract: Edge machine learning presents a unique set of constraints not encountered in cloud-scale model deployment: strict memory budgets, limited compute, and

PhyDetEx: Detecting and Explaining the Physical Plausibility of T2V Models

arXiv:2512.01843v2 Announce Type: replace Abstract: Driven by the growing capacity and training scale, Text-to-Video (T2V) generation models have recently achieved substantial progress in video qualit

Position: Early-Stage Quality Assurance in Annotation Pipelines Is More Cost-Effective Than Late-Stage Validation

arXiv:2605.15714v1 Announce Type: cross Abstract: This position paper argues that the machine learning community should prioritize early-stage quality assurance in annotation pipelines over the prevai

Position: Ideas Should be the Center of Machine Learning Research

arXiv:2605.15253v1 Announce Type: new Abstract: Machine learning research increasingly bifurcates into two disconnected modes: benchmark-driven engineering that prioritizes metrics over understanding,

Probabilistic Dating of Historical Manuscripts via Evidential Deep Regression on Visual Script Features

arXiv:2605.06475v1 Announce Type: cross Abstract: We introduce a probabilistic approach for dating historical manuscript pages from visual features alone. Instead of aggregating centuries into classes